Purchasing Behavior Analysis Model that Considers the Relationship Between Topic Hierarchy and Item Categories

Yuta Sakai*, Yui Matsuoka, Masayuki Goto

*この研究の対応する著者

研究成果: Conference contribution

抄録

With the spread of EC sites, it has become an important work for companies to analyze user preferences contained in accumulated purchase history data and utilize them in marketing measures. A topic model is well known as a method for analyzing user preferences from purchase history data, and a model assuming hierarchy of topics has been proposed as an extension method. The previously proposed PAM (Pachinko Allocation Model) is a highly expressive model in which all upper and lower topics are connected by a network and the relationships between multiple topics can be analyzed. However, PAM is easily affected by the initial values of learning parameters, and it is difficult to obtain stable topics, so the interpretation of the estimated topics becomes unstable. It is dangerous to make business decisions based on the interpretation of such unstable results. Therefore, in this research, instead of using the hierarchy of topics estimated based on the user’s purchasing behavior, we use information with a hierarchical structure of “product categories” given by the EC site for managing items. Therefore, we propose a method that is useful for studying measures and that enables hierarchical topic analysis. Finally, the proposed method is applied to the evaluation history data of the actual EC site to analyze the user’s preference and show its usefulness.

本文言語English
ホスト出版物のタイトルSocial Computing and Social Media
ホスト出版物のサブタイトルApplications in Education and Commerce - 14th International Conference, SCSM 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
編集者Gabriele Meiselwitz
出版社Springer Science and Business Media Deutschland GmbH
ページ344-358
ページ数15
ISBN(印刷版)9783031050633
DOI
出版ステータスPublished - 2022
イベント14th International Conference on Social Computing and Social Media, SCSM 2022 Held as Part of the 24th HCI International Conference, HCII 2022 - Virtual, Online
継続期間: 2022 6月 262022 7月 1

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13316 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference14th International Conference on Social Computing and Social Media, SCSM 2022 Held as Part of the 24th HCI International Conference, HCII 2022
CityVirtual, Online
Period22/6/2622/7/1

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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